Computer Science > Computational Geometry

Title:Epsilon-approximations and epsilon-nets

Abstract: The use of random samples to approximate properties of geometric
configurations has been an influential idea for both combinatorial and
algorithmic purposes. This chapter considers two related
notions---$ε$-approximations and $ε$-nets---that capture the most
important quantitative properties that one would expect from a random sample
with respect to an underlying geometric configuration.